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HUB FOR
METABOLIC PSYCHIATRY

Working at the interface of mental and physical health.
Funded by UKRI as part of the Mental Health Platform.

Our Vision

To achieve a step change in UK research activity and clinical innovation in Metabolic Psychiatry.

Our core aims:

To drive discovery science in metabolic psychiatry.
To co-produce and test novel metabolism-based treatment approaches with people with lived experience.
To build UK-wide capacity for metabolic psychiatry research and clinical innovation.

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The Hub for Metabolic Psychiatry: 6 workstreams working together to advance our understanding of the connection between metabolic and mental health.

1. GENOMICS AND CAUSAL INFERENCE

We assess bi-directional causal associations between SMI and metabolic dysfunction in large genomic datasets and seek to uncover shared genetic architecture.

2. HEALTH INFORMATICS AND DATA SCIENCE

We harness advances in machine learning to analyse large health datasets and explore novel insights into metabolic phenotypes in SMI. We seek to identify individuals and groups at high-risk of cardiometabolic disease and poor clinical outcomes.

3. METABOLIC BIOMARKERS

We will identify metabolomic biomarkers of serious mental illness and conduct a deep-phenotyping 12-month prospective study to assess how changes in metabolic profile relate to clinical and functional outcomes.

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HUB FOR METABOLIC PSYCHIATRY

4. PATIENT PRIORITISED TESTING OF METABOLIC INTERVENTIONS

We work closely with people with lived experience to identify established and emerging interventions which target metabolic dysfunction to improve psychiatric and medical outcomes in people with serious mental illness. These patient-priorities feed into pilot studies which seek to uncover new treatment modalities for serious mental illness.

The Hub In Numbers

970M

PEOPLE LIVING WITH A MENTAL DISORDER

>1B

PEOPLE LIVING WITH METABOLIC SYNDROME

462M

PEOPLE LIVING WITH TYPE 2 DIABETES

2/3

DEATHS IN PEOPLE WITH SERIOUS MENTAL ILLNESS DUE TO PHYSICAL ILLNESS

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5. AI AND MACHINE LEARNING

We integrate advances in machine learning analysis across all workstreams to gain deep insight into the data. A data curation and data sharing platform will allow us to maximise the open science opportunities of this work.

6. PATIENT AND PUBLIC INVOLVEMENT AND ENGAGEMENT

Working closely with the McPin foundation we ensure that patient priorities are at the heart of all of our research. We are committed to meaningful, impactful and measurable input from people with lived experience at every stage of the research process.

A group on people working on laptops at a desk.Image by Annie Spratt